Canonical Correlation Analysis to relate a Genomic Dataset with a Neuroimage Dataset.

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dc.contributor.advisorMcIntyre, M.
dc.contributor.advisorAdu-Gyamfi, D.
dc.contributor.authorAnnan, A.
dc.contributor.otherUniversity of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Mathematics
dc.date.accessioned2017-01-17T14:31:44Z
dc.date.accessioned2017-10-13T17:37:50Z
dc.date.available2017-01-17T14:31:44Z
dc.date.available2017-10-13T17:37:50Z
dc.date.issued2016-07
dc.descriptionThesis(MPHIL)-University of Ghana, 2016
dc.description.abstractThis thesis investigates the relationship between copy number variations and neuro-image features of Glioblastoma patients. Canonical correlation analysis was employed to elicit these relationships. This thesis highlights some of the concepts of the technique which enabled us to obtain our main results. We found three pairs of significant canonical variates with correlations of 0:6704;0:6347 and 0:5552 respectively, which was used to identify genes and neuro-image features related to Glioblastoma.en_US
dc.format.extentIx, 71p: ill
dc.identifier.urihttp://197.255.68.203/handle/123456789/21343
dc.language.isoenen_US
dc.publisherUniversity of Ghanaen_US
dc.rights.holderUniversity of Ghana
dc.subjectCanonical Correlation Analysisen_US
dc.subjectGenomic Dataseten_US
dc.subjectNeuroimage Dataseten_US
dc.titleCanonical Correlation Analysis to relate a Genomic Dataset with a Neuroimage Dataset.en_US
dc.typeThesisen_US

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